Network Security White Papers
Transductive Link Spam Detection
Overview Web spam can significantly deteriorate the quality of search engines. Early web spamming techniques mainly manipulate page content. Since linkage information is widely used in web search, link-based spamming has also developed. So far, many techniques have been proposed to detect link spam. Those approaches are basically variants of link-based web ranking methods. In contrast, the paper cast the link spam detection problem into a machine learning problem of classification on directed graphs. This paper develops discrete analysis on directed graphs, and constructs a discrete analogue of classical regularization theory via discrete analysis. A classification algorithm for directed graphs is then derived from the discrete regularization. This paper has applied the approach to real-world link spam detection problems, and encouraging results have been obtained.
| Publisher | Association for Computing Machinery | File Format | |
|---|---|---|---|
| Date Published | May 2007 | ||
| Format | White Papers | ||
| Topics | |||
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